title: Linear parameter varying identification of ankle joint intrinsic stiffness during imposed walking movements.
abstract: This paper describes a novel model structure and identification method for the time-varying, intrinsic stiffness of human ankle joint during imposed walking (IW) movements. The model structure is based on the superposition of a large signal, linear, time-invariant (LTI) model and a small signal linear-parameter varying (LPV) model. The methodology is based on a two-step algorithm; the LTI model is first estimated using data from an unperturbed IW trial. Then, the LPV model is identified using data from a perturbed IW trial with the output predictions of the LTI model removed from the measured torque. Experimental results demonstrate that the method accurately tracks the continuous-time variation of normal ankle intrinsic stiffness when the joint position changes during the IW movement. Intrinsic stiffness gain decreases from full plantarflexion to near the mid-point of plantarflexion and then increases substantially as the ankle is dosriflexed.
authors.forename: Ehsan
authors.initials: E
authors.lastname: Sobhani Tehrani
authors.forename: Kian
authors.initials: K
authors.lastname: Jalaleddini
authors.forename: Robert E
authors.initials: RE
authors.lastname: Kearney
mesh_terms: D000465:Algorithms; D000842:Ankle / Q000502:physiology; D000843:Ankle Joint / Q000502:physiology*; D001696:Biomechanical Phenomena; D003198:Computer Simulation; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D007592:Joint Diseases / Q000503:physiopathology; D016014:Linear Models; D008297:Male; D018670:Monitoring, Ambulatory / Q000295:instrumentation / Q000379:methods*; D015203:Reproducibility of Results; D019415:Torque; D016138:Walking / Q000502:physiology*